Overview

Brought to you by YData

Dataset statistics

Number of variables33
Number of observations4733
Missing cells10482
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory264.0 B

Variable types

Numeric8
Text10
Categorical6
DateTime4
Unsupported5

Alerts

airdate is highly overall correlated with extraction_dateHigh correlation
extraction_date is highly overall correlated with airdateHigh correlation
number is highly overall correlated with typeHigh correlation
runtime is highly overall correlated with show_averageRuntimeHigh correlation
season is highly overall correlated with show_typeHigh correlation
show_averageRuntime is highly overall correlated with runtimeHigh correlation
show_id is highly overall correlated with show_weightHigh correlation
show_language is highly overall correlated with show_statusHigh correlation
show_status is highly overall correlated with show_language and 1 other fieldsHigh correlation
show_type is highly overall correlated with season and 1 other fieldsHigh correlation
show_weight is highly overall correlated with show_idHigh correlation
type is highly overall correlated with numberHigh correlation
type is highly imbalanced (96.2%) Imbalance
airtime has 2428 (51.3%) missing values Missing
show_ended has 3037 (64.2%) missing values Missing
show_network has 4217 (89.1%) missing values Missing
show_summary has 771 (16.3%) missing values Missing
id has unique values Unique
url has unique values Unique
links_self has unique values Unique
rating is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_rating is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_network is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_links is an unsupported type, check if it needs cleaning or further analysis Unsupported
show_weight has 138 (2.9%) zeros Zeros

Reproduction

Analysis started2024-10-31 09:37:29.466450
Analysis finished2024-10-31 09:37:44.147365
Duration14.68 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

Unique 

Distinct4733
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2767629.8
Minimum2391730
Maximum3037097
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:44.257105image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2391730
5-th percentile2693704.6
Q12732495
median2744331
Q32775823
95-th percentile2921731.4
Maximum3037097
Range645367
Interquartile range (IQR)43328

Descriptive statistics

Standard deviation69337.578
Coefficient of variation (CV)0.025053054
Kurtosis2.612156
Mean2767629.8
Median Absolute Deviation (MAD)14503
Skewness1.5647251
Sum1.3099192 × 1010
Variance4.8076997 × 109
MonotonicityNot monotonic
2024-10-31T04:37:44.443755image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2751926 1
 
< 0.1%
2730586 1
 
< 0.1%
2730587 1
 
< 0.1%
2730588 1
 
< 0.1%
2730589 1
 
< 0.1%
2730590 1
 
< 0.1%
2730591 1
 
< 0.1%
2730592 1
 
< 0.1%
2730593 1
 
< 0.1%
2730594 1
 
< 0.1%
Other values (4723) 4723
99.8%
ValueCountFrequency (%)
2391730 1
< 0.1%
2494160 1
< 0.1%
2580338 1
< 0.1%
2580339 1
< 0.1%
2610881 1
< 0.1%
2610882 1
< 0.1%
2625941 1
< 0.1%
2633274 1
< 0.1%
2633275 1
< 0.1%
2633276 1
< 0.1%
ValueCountFrequency (%)
3037097 1
< 0.1%
3034747 1
< 0.1%
3034745 1
< 0.1%
3032636 1
< 0.1%
3032635 1
< 0.1%
3030200 1
< 0.1%
3030199 1
< 0.1%
3030198 1
< 0.1%
3030197 1
< 0.1%
3030124 1
< 0.1%

url
Text

Unique 

Distinct4733
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:44.755869image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length192
Median length147
Mean length79.07416
Min length53

Characters and Unicode

Total characters374258
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4733 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1
2nd rowhttps://www.tvmaze.com/episodes/2730587/neznost-2x02-seria-2
3rd rowhttps://www.tvmaze.com/episodes/2730588/neznost-2x03-seria-3
4th rowhttps://www.tvmaze.com/episodes/2730589/neznost-2x04-seria-4
5th rowhttps://www.tvmaze.com/episodes/2730590/neznost-2x05-seria-5
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2692646/nedetskoe-kino-1x01-seria-1 1
 
< 0.1%
https://www.tvmaze.com/episodes/2751926/the-tonight-show-starring-jimmy-fallon-2024-01-31-arnold-schwarzenegger-kathryn-newton-the-lemon-twigs 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730587/neznost-2x02-seria-2 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730588/neznost-2x03-seria-3 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730589/neznost-2x04-seria-4 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730590/neznost-2x05-seria-5 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730591/neznost-2x06-seria-6 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730592/neznost-2x07-seria-7 1
 
< 0.1%
https://www.tvmaze.com/episodes/2730593/neznost-2x08-seria-8 1
 
< 0.1%
Other values (4723) 4723
99.8%
2024-10-31T04:37:45.441312image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 31552
 
8.4%
- 29531
 
7.9%
s 24031
 
6.4%
/ 23665
 
6.3%
t 21578
 
5.8%
o 20054
 
5.4%
w 16225
 
4.3%
a 14910
 
4.0%
i 14871
 
4.0%
p 14136
 
3.8%
Other values (30) 163705
43.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 374258
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 31552
 
8.4%
- 29531
 
7.9%
s 24031
 
6.4%
/ 23665
 
6.3%
t 21578
 
5.8%
o 20054
 
5.4%
w 16225
 
4.3%
a 14910
 
4.0%
i 14871
 
4.0%
p 14136
 
3.8%
Other values (30) 163705
43.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 374258
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 31552
 
8.4%
- 29531
 
7.9%
s 24031
 
6.4%
/ 23665
 
6.3%
t 21578
 
5.8%
o 20054
 
5.4%
w 16225
 
4.3%
a 14910
 
4.0%
i 14871
 
4.0%
p 14136
 
3.8%
Other values (30) 163705
43.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 374258
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 31552
 
8.4%
- 29531
 
7.9%
s 24031
 
6.4%
/ 23665
 
6.3%
t 21578
 
5.8%
o 20054
 
5.4%
w 16225
 
4.3%
a 14910
 
4.0%
i 14871
 
4.0%
p 14136
 
3.8%
Other values (30) 163705
43.7%

name
Text

Distinct2346
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:45.920033image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length129
Median length121
Mean length14.983097
Min length2

Characters and Unicode

Total characters70915
Distinct characters436
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2157 ?
Unique (%)45.6%

Sample

1st rowСерия 1
2nd rowСерия 2
3rd rowСерия 3
4th rowСерия 4
5th rowСерия 5
ValueCountFrequency (%)
episode 2443
 
18.3%
the 382
 
2.9%
1 190
 
1.4%
2 189
 
1.4%
серия 180
 
1.3%
3 156
 
1.2%
4 147
 
1.1%
141
 
1.1%
5 134
 
1.0%
6 128
 
1.0%
Other values (4313) 9283
69.4%
2024-10-31T04:37:46.543593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8648
 
12.2%
e 5825
 
8.2%
o 4550
 
6.4%
i 4389
 
6.2%
s 4071
 
5.7%
d 3382
 
4.8%
p 2913
 
4.1%
E 2761
 
3.9%
a 2552
 
3.6%
n 2124
 
3.0%
Other values (426) 29700
41.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70915
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8648
 
12.2%
e 5825
 
8.2%
o 4550
 
6.4%
i 4389
 
6.2%
s 4071
 
5.7%
d 3382
 
4.8%
p 2913
 
4.1%
E 2761
 
3.9%
a 2552
 
3.6%
n 2124
 
3.0%
Other values (426) 29700
41.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70915
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8648
 
12.2%
e 5825
 
8.2%
o 4550
 
6.4%
i 4389
 
6.2%
s 4071
 
5.7%
d 3382
 
4.8%
p 2913
 
4.1%
E 2761
 
3.9%
a 2552
 
3.6%
n 2124
 
3.0%
Other values (426) 29700
41.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70915
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8648
 
12.2%
e 5825
 
8.2%
o 4550
 
6.4%
i 4389
 
6.2%
s 4071
 
5.7%
d 3382
 
4.8%
p 2913
 
4.1%
E 2761
 
3.9%
a 2552
 
3.6%
n 2124
 
3.0%
Other values (426) 29700
41.9%

season
Real number (ℝ)

High correlation 

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean301.31206
Minimum1
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:46.701171image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q36
95-th percentile2024
Maximum2024
Range2023
Interquartile range (IQR)5

Descriptive statistics

Standard deviation716.58869
Coefficient of variation (CV)2.3782277
Kurtosis1.95659
Mean301.31206
Median Absolute Deviation (MAD)0
Skewness1.9887936
Sum1426110
Variance513499.35
MonotonicityNot monotonic
2024-10-31T04:37:46.873677image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 2500
52.8%
2024 694
 
14.7%
2 547
 
11.6%
3 259
 
5.5%
4 112
 
2.4%
5 104
 
2.2%
6 73
 
1.5%
8 65
 
1.4%
25 36
 
0.8%
11 33
 
0.7%
Other values (24) 310
 
6.5%
ValueCountFrequency (%)
1 2500
52.8%
2 547
 
11.6%
3 259
 
5.5%
4 112
 
2.4%
5 104
 
2.2%
6 73
 
1.5%
7 25
 
0.5%
8 65
 
1.4%
9 27
 
0.6%
10 26
 
0.5%
ValueCountFrequency (%)
2024 694
14.7%
2023 4
 
0.1%
54 4
 
0.1%
50 3
 
0.1%
41 8
 
0.2%
39 19
 
0.4%
34 4
 
0.1%
31 5
 
0.1%
30 20
 
0.4%
27 6
 
0.1%

number
Real number (ℝ)

High correlation 

Distinct183
Distinct (%)3.9%
Missing29
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean19.133503
Minimum1
Maximum959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:47.092056image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q318
95-th percentile67
Maximum959
Range958
Interquartile range (IQR)14

Descriptive statistics

Standard deviation47.937016
Coefficient of variation (CV)2.5053967
Kurtosis174.05576
Mean19.133503
Median Absolute Deviation (MAD)6
Skewness11.026564
Sum90004
Variance2297.9575
MonotonicityNot monotonic
2024-10-31T04:37:47.307134image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 395
 
8.3%
2 369
 
7.8%
3 349
 
7.4%
4 310
 
6.5%
5 273
 
5.8%
6 255
 
5.4%
7 214
 
4.5%
8 203
 
4.3%
9 156
 
3.3%
10 145
 
3.1%
Other values (173) 2035
43.0%
ValueCountFrequency (%)
1 395
8.3%
2 369
7.8%
3 349
7.4%
4 310
6.5%
5 273
5.8%
6 255
5.4%
7 214
4.5%
8 203
4.3%
9 156
 
3.3%
10 145
 
3.1%
ValueCountFrequency (%)
959 1
< 0.1%
958 1
< 0.1%
957 1
< 0.1%
956 1
< 0.1%
955 1
< 0.1%
407 1
< 0.1%
406 1
< 0.1%
405 1
< 0.1%
404 1
< 0.1%
403 1
< 0.1%

type
Categorical

High correlation  Imbalance 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
regular
4704 
significant_special
 
18
insignificant_special
 
11

Length

Max length21
Median length7
Mean length7.0781745
Min length7

Characters and Unicode

Total characters33501
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular 4704
99.4%
significant_special 18
 
0.4%
insignificant_special 11
 
0.2%

Length

2024-10-31T04:37:47.509534image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-31T04:37:47.638184image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 4704
99.4%
significant_special 18
 
0.4%
insignificant_special 11
 
0.2%

Most occurring characters

ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33501
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33501
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33501
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

airdate
Categorical

High correlation 

Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-01-26
 
301
2024-01-19
 
265
2024-01-11
 
230
2024-01-18
 
217
2024-01-25
 
214
Other values (26)
3506 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters47330
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-01
2nd row2024-01-01
3rd row2024-01-01
4th row2024-01-01
5th row2024-01-01

Common Values

ValueCountFrequency (%)
2024-01-26 301
 
6.4%
2024-01-19 265
 
5.6%
2024-01-11 230
 
4.9%
2024-01-18 217
 
4.6%
2024-01-25 214
 
4.5%
2024-01-08 210
 
4.4%
2024-01-22 190
 
4.0%
2024-01-01 188
 
4.0%
2024-01-24 179
 
3.8%
2024-01-04 173
 
3.7%
Other values (21) 2566
54.2%

Length

2024-10-31T04:37:47.781781image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-01-26 301
 
6.4%
2024-01-19 265
 
5.6%
2024-01-11 230
 
4.9%
2024-01-18 217
 
4.6%
2024-01-25 214
 
4.5%
2024-01-08 210
 
4.4%
2024-01-22 190
 
4.0%
2024-01-01 188
 
4.0%
2024-01-24 179
 
3.8%
2024-01-04 173
 
3.7%
Other values (21) 2566
54.2%

Most occurring characters

ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 47330
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 47330
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 47330
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

airtime
Date

Missing 

Distinct65
Distinct (%)2.8%
Missing2428
Missing (%)51.3%
Memory size37.1 KiB
Minimum2024-10-31 00:00:00
Maximum2024-10-31 23:35:00
2024-10-31T04:37:47.951495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:48.146974image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct855
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
Minimum2024-01-01 00:00:00+00:00
Maximum2024-02-01 04:35:00+00:00
2024-10-31T04:37:48.337473image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:48.558947image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

runtime
Real number (ℝ)

High correlation 

Distinct109
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.401026
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:48.751467image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q121
median43
Q347
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)26

Descriptive statistics

Standard deviation41.601936
Coefficient of variation (CV)0.9369589
Kurtosis13.235542
Mean44.401026
Median Absolute Deviation (MAD)15
Skewness3.2241809
Sum210150.06
Variance1730.7211
MonotonicityNot monotonic
2024-10-31T04:37:48.926998image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 578
 
12.2%
44.40102588 444
 
9.4%
15 314
 
6.6%
60 304
 
6.4%
30 205
 
4.3%
10 181
 
3.8%
120 142
 
3.0%
40 116
 
2.5%
12 116
 
2.5%
3 116
 
2.5%
Other values (99) 2217
46.8%
ValueCountFrequency (%)
1 7
 
0.1%
2 43
 
0.9%
3 116
2.5%
4 4
 
0.1%
5 41
 
0.9%
6 17
 
0.4%
7 39
 
0.8%
8 47
 
1.0%
9 17
 
0.4%
10 181
3.8%
ValueCountFrequency (%)
300 23
 
0.5%
240 71
1.5%
210 3
 
0.1%
205 1
 
< 0.1%
180 35
0.7%
173 1
 
< 0.1%
159 27
 
0.6%
150 3
 
0.1%
149 1
 
< 0.1%
142 2
 
< 0.1%

rating
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.1 KiB
Distinct1460
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:49.380752image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length2299
Median length20
Mean length78.457427
Min length20

Characters and Unicode

Total characters371339
Distinct characters163
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1453 ?
Unique (%)30.7%

Sample

1st rowNo summary available
2nd rowNo summary available
3rd rowNo summary available
4th rowNo summary available
5th rowNo summary available
ValueCountFrequency (%)
no 3293
 
5.5%
available 3269
 
5.4%
summary 3268
 
5.4%
the 2665
 
4.4%
and 1704
 
2.8%
a 1684
 
2.8%
to 1657
 
2.8%
of 967
 
1.6%
in 800
 
1.3%
with 552
 
0.9%
Other values (11259) 40226
66.9%
2024-10-31T04:37:50.179996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55199
14.9%
a 32907
 
8.9%
e 31258
 
8.4%
i 20217
 
5.4%
o 19644
 
5.3%
s 19446
 
5.2%
t 19357
 
5.2%
r 17818
 
4.8%
n 16925
 
4.6%
l 15740
 
4.2%
Other values (153) 122828
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 371339
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
55199
14.9%
a 32907
 
8.9%
e 31258
 
8.4%
i 20217
 
5.4%
o 19644
 
5.3%
s 19446
 
5.2%
t 19357
 
5.2%
r 17818
 
4.8%
n 16925
 
4.6%
l 15740
 
4.2%
Other values (153) 122828
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 371339
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
55199
14.9%
a 32907
 
8.9%
e 31258
 
8.4%
i 20217
 
5.4%
o 19644
 
5.3%
s 19446
 
5.2%
t 19357
 
5.2%
r 17818
 
4.8%
n 16925
 
4.6%
l 15740
 
4.2%
Other values (153) 122828
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 371339
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
55199
14.9%
a 32907
 
8.9%
e 31258
 
8.4%
i 20217
 
5.4%
o 19644
 
5.3%
s 19446
 
5.2%
t 19357
 
5.2%
r 17818
 
4.8%
n 16925
 
4.6%
l 15740
 
4.2%
Other values (153) 122828
33.1%

links_self
Text

Unique 

Distinct4733
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:50.465618image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters184587
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4733 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2730586
2nd rowhttps://api.tvmaze.com/episodes/2730587
3rd rowhttps://api.tvmaze.com/episodes/2730588
4th rowhttps://api.tvmaze.com/episodes/2730589
5th rowhttps://api.tvmaze.com/episodes/2730590
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2692646 1
 
< 0.1%
https://api.tvmaze.com/episodes/2751926 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730586 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730587 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730588 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730589 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730590 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730591 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730592 1
 
< 0.1%
https://api.tvmaze.com/episodes/2730593 1
 
< 0.1%
Other values (4723) 4723
99.8%
2024-10-31T04:37:50.855875image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 18932
 
10.3%
t 14199
 
7.7%
s 14199
 
7.7%
p 14199
 
7.7%
e 14199
 
7.7%
. 9466
 
5.1%
i 9466
 
5.1%
o 9466
 
5.1%
m 9466
 
5.1%
a 9466
 
5.1%
Other values (16) 61529
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 184587
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 18932
 
10.3%
t 14199
 
7.7%
s 14199
 
7.7%
p 14199
 
7.7%
e 14199
 
7.7%
. 9466
 
5.1%
i 9466
 
5.1%
o 9466
 
5.1%
m 9466
 
5.1%
a 9466
 
5.1%
Other values (16) 61529
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 184587
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 18932
 
10.3%
t 14199
 
7.7%
s 14199
 
7.7%
p 14199
 
7.7%
e 14199
 
7.7%
. 9466
 
5.1%
i 9466
 
5.1%
o 9466
 
5.1%
m 9466
 
5.1%
a 9466
 
5.1%
Other values (16) 61529
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 184587
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 18932
 
10.3%
t 14199
 
7.7%
s 14199
 
7.7%
p 14199
 
7.7%
e 14199
 
7.7%
. 9466
 
5.1%
i 9466
 
5.1%
o 9466
 
5.1%
m 9466
 
5.1%
a 9466
 
5.1%
Other values (16) 61529
33.3%
Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:51.151871image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length33.935981
Min length32

Characters and Unicode

Total characters160619
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.8%

Sample

1st rowhttps://api.tvmaze.com/shows/51908
2nd rowhttps://api.tvmaze.com/shows/51908
3rd rowhttps://api.tvmaze.com/shows/51908
4th rowhttps://api.tvmaze.com/shows/51908
5th rowhttps://api.tvmaze.com/shows/51908
ValueCountFrequency (%)
https://api.tvmaze.com/shows/78854 100
 
2.1%
https://api.tvmaze.com/shows/73952 38
 
0.8%
https://api.tvmaze.com/shows/73703 36
 
0.8%
https://api.tvmaze.com/shows/72654 36
 
0.8%
https://api.tvmaze.com/shows/73773 36
 
0.8%
https://api.tvmaze.com/shows/74045 34
 
0.7%
https://api.tvmaze.com/shows/42056 33
 
0.7%
https://api.tvmaze.com/shows/69806 32
 
0.7%
https://api.tvmaze.com/shows/73931 30
 
0.6%
https://api.tvmaze.com/shows/74100 28
 
0.6%
Other values (671) 4330
91.5%
2024-10-31T04:37:51.634977image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 18932
 
11.8%
t 14199
 
8.8%
s 14199
 
8.8%
h 9466
 
5.9%
p 9466
 
5.9%
a 9466
 
5.9%
. 9466
 
5.9%
m 9466
 
5.9%
o 9466
 
5.9%
: 4733
 
2.9%
Other values (16) 51760
32.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 160619
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 18932
 
11.8%
t 14199
 
8.8%
s 14199
 
8.8%
h 9466
 
5.9%
p 9466
 
5.9%
a 9466
 
5.9%
. 9466
 
5.9%
m 9466
 
5.9%
o 9466
 
5.9%
: 4733
 
2.9%
Other values (16) 51760
32.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 160619
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 18932
 
11.8%
t 14199
 
8.8%
s 14199
 
8.8%
h 9466
 
5.9%
p 9466
 
5.9%
a 9466
 
5.9%
. 9466
 
5.9%
m 9466
 
5.9%
o 9466
 
5.9%
: 4733
 
2.9%
Other values (16) 51760
32.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 160619
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 18932
 
11.8%
t 14199
 
8.8%
s 14199
 
8.8%
h 9466
 
5.9%
p 9466
 
5.9%
a 9466
 
5.9%
. 9466
 
5.9%
m 9466
 
5.9%
o 9466
 
5.9%
: 4733
 
2.9%
Other values (16) 51760
32.2%
Distinct679
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:52.046542image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length63
Median length41
Mean length17.485527
Min length2

Characters and Unicode

Total characters82759
Distinct characters167
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.8%

Sample

1st rowНежность
2nd rowНежность
3rd rowНежность
4th rowНежность
5th rowНежность
ValueCountFrequency (%)
the 777
 
5.2%
of 340
 
2.3%
my 226
 
1.5%
love 179
 
1.2%
news 171
 
1.2%
a 169
 
1.1%
and 160
 
1.1%
with 130
 
0.9%
you 122
 
0.8%
world 108
 
0.7%
Other values (1394) 12453
83.9%
2024-10-31T04:37:52.649919image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 82759
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 82759
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 82759
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

show_id
Real number (ℝ)

High correlation 

Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63465.946
Minimum274
Maximum80412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:52.821317image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum274
5-th percentile11836.8
Q159613
median72501
Q374045
95-th percentile77398.2
Maximum80412
Range80138
Interquartile range (IQR)14432

Descriptive statistics

Standard deviation18711.733
Coefficient of variation (CV)0.29483108
Kurtosis3.2219027
Mean63465.946
Median Absolute Deviation (MAD)3716
Skewness-1.9800069
Sum3.0038432 × 108
Variance3.5012897 × 108
MonotonicityNot monotonic
2024-10-31T04:37:53.002831image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78854 100
 
2.1%
73952 38
 
0.8%
72654 36
 
0.8%
73773 36
 
0.8%
73703 36
 
0.8%
74045 34
 
0.7%
42056 33
 
0.7%
69806 32
 
0.7%
73931 30
 
0.6%
73862 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
274 6
 
0.1%
703 4
 
0.1%
718 17
0.4%
729 4
 
0.1%
793 19
0.4%
802 5
 
0.1%
812 23
0.5%
875 3
 
0.1%
920 8
 
0.2%
938 6
 
0.1%
ValueCountFrequency (%)
80412 1
 
< 0.1%
80352 2
 
< 0.1%
80138 4
 
0.1%
80137 2
 
< 0.1%
79953 2
 
< 0.1%
79903 23
 
0.5%
79454 8
 
0.2%
79449 1
 
< 0.1%
78906 2
 
< 0.1%
78854 100
2.1%
Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:53.307115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length97
Median length73
Mean length52.204521
Min length35

Characters and Unicode

Total characters247084
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.8%

Sample

1st rowhttps://www.tvmaze.com/shows/51908/neznost
2nd rowhttps://www.tvmaze.com/shows/51908/neznost
3rd rowhttps://www.tvmaze.com/shows/51908/neznost
4th rowhttps://www.tvmaze.com/shows/51908/neznost
5th rowhttps://www.tvmaze.com/shows/51908/neznost
ValueCountFrequency (%)
https://www.tvmaze.com/shows/78854/my-beautiful-dumb-wife 100
 
2.1%
https://www.tvmaze.com/shows/73952/shanghai-picked-flowers 38
 
0.8%
https://www.tvmaze.com/shows/73703/just-between-us 36
 
0.8%
https://www.tvmaze.com/shows/72654/our-interpreter 36
 
0.8%
https://www.tvmaze.com/shows/73773/my-boss 36
 
0.8%
https://www.tvmaze.com/shows/74045/sword-and-fairy-4 34
 
0.7%
https://www.tvmaze.com/shows/42056/like-a-flowing-river 33
 
0.7%
https://www.tvmaze.com/shows/69806/scout-hero 32
 
0.7%
https://www.tvmaze.com/shows/73931/different-princess 30
 
0.6%
https://www.tvmaze.com/shows/74100/small-town-stories 28
 
0.6%
Other values (671) 4330
91.5%
2024-10-31T04:37:53.779052image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 23665
 
9.6%
w 20431
 
8.3%
t 18934
 
7.7%
s 18903
 
7.7%
o 14745
 
6.0%
e 12815
 
5.2%
h 12412
 
5.0%
m 11603
 
4.7%
a 11005
 
4.5%
- 10058
 
4.1%
Other values (30) 92513
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 247084
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 23665
 
9.6%
w 20431
 
8.3%
t 18934
 
7.7%
s 18903
 
7.7%
o 14745
 
6.0%
e 12815
 
5.2%
h 12412
 
5.0%
m 11603
 
4.7%
a 11005
 
4.5%
- 10058
 
4.1%
Other values (30) 92513
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 247084
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 23665
 
9.6%
w 20431
 
8.3%
t 18934
 
7.7%
s 18903
 
7.7%
o 14745
 
6.0%
e 12815
 
5.2%
h 12412
 
5.0%
m 11603
 
4.7%
a 11005
 
4.5%
- 10058
 
4.1%
Other values (30) 92513
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 247084
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 23665
 
9.6%
w 20431
 
8.3%
t 18934
 
7.7%
s 18903
 
7.7%
o 14745
 
6.0%
e 12815
 
5.2%
h 12412
 
5.0%
m 11603
 
4.7%
a 11005
 
4.5%
- 10058
 
4.1%
Other values (30) 92513
37.4%
Distinct679
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:54.158395image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length63
Median length41
Mean length17.485527
Min length2

Characters and Unicode

Total characters82759
Distinct characters167
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.8%

Sample

1st rowНежность
2nd rowНежность
3rd rowНежность
4th rowНежность
5th rowНежность
ValueCountFrequency (%)
the 777
 
5.2%
of 340
 
2.3%
my 226
 
1.5%
love 179
 
1.2%
news 171
 
1.2%
a 169
 
1.1%
and 160
 
1.1%
with 130
 
0.9%
you 122
 
0.8%
world 108
 
0.7%
Other values (1394) 12453
83.9%
2024-10-31T04:37:54.741869image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 82759
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 82759
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 82759
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

show_type
Categorical

High correlation 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
Scripted
2216 
Animation
643 
News
534 
Reality
499 
Documentary
324 
Other values (6)
517 

Length

Max length11
Median length10
Mean length7.8396366
Min length4

Characters and Unicode

Total characters37105
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowScripted
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted 2216
46.8%
Animation 643
 
13.6%
News 534
 
11.3%
Reality 499
 
10.5%
Documentary 324
 
6.8%
Talk Show 279
 
5.9%
Game Show 114
 
2.4%
Variety 56
 
1.2%
Sports 53
 
1.1%
Panel Show 14
 
0.3%

Length

2024-10-31T04:37:54.914854image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scripted 2216
43.1%
animation 643
 
12.5%
news 534
 
10.4%
reality 499
 
9.7%
show 408
 
7.9%
documentary 324
 
6.3%
talk 279
 
5.4%
game 114
 
2.2%
variety 56
 
1.1%
sports 53
 
1.0%
Other values (2) 15
 
0.3%

Most occurring characters

ValueCountFrequency (%)
i 4057
10.9%
t 3791
 
10.2%
e 3757
 
10.1%
S 2677
 
7.2%
r 2650
 
7.1%
c 2540
 
6.8%
p 2269
 
6.1%
d 2217
 
6.0%
a 1930
 
5.2%
n 1624
 
4.4%
Other values (18) 9593
25.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37105
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 4057
10.9%
t 3791
 
10.2%
e 3757
 
10.1%
S 2677
 
7.2%
r 2650
 
7.1%
c 2540
 
6.8%
p 2269
 
6.1%
d 2217
 
6.0%
a 1930
 
5.2%
n 1624
 
4.4%
Other values (18) 9593
25.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37105
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 4057
10.9%
t 3791
 
10.2%
e 3757
 
10.1%
S 2677
 
7.2%
r 2650
 
7.1%
c 2540
 
6.8%
p 2269
 
6.1%
d 2217
 
6.0%
a 1930
 
5.2%
n 1624
 
4.4%
Other values (18) 9593
25.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37105
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 4057
10.9%
t 3791
 
10.2%
e 3757
 
10.1%
S 2677
 
7.2%
r 2650
 
7.1%
c 2540
 
6.8%
p 2269
 
6.1%
d 2217
 
6.0%
a 1930
 
5.2%
n 1624
 
4.4%
Other values (18) 9593
25.9%

show_language
Categorical

High correlation 

Distinct33
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
english
1945 
chinese
1506 
russian
242 
norwegian
 
177
korean
 
106
Other values (28)
757 

Length

Max length10
Median length7
Mean length6.9964082
Min length4

Characters and Unicode

Total characters33114
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowrussian
2nd rowrussian
3rd rowrussian
4th rowrussian
5th rowrussian

Common Values

ValueCountFrequency (%)
english 1945
41.1%
chinese 1506
31.8%
russian 242
 
5.1%
norwegian 177
 
3.7%
korean 106
 
2.2%
spanish 86
 
1.8%
arabic 76
 
1.6%
swedish 73
 
1.5%
japanese 69
 
1.5%
hindi 66
 
1.4%
Other values (23) 387
 
8.2%

Length

2024-10-31T04:37:55.068412image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english 1945
41.1%
chinese 1506
31.8%
russian 242
 
5.1%
norwegian 177
 
3.7%
korean 106
 
2.2%
spanish 86
 
1.8%
arabic 76
 
1.6%
swedish 73
 
1.5%
japanese 69
 
1.5%
hindi 66
 
1.4%
Other values (23) 387
 
8.2%

Most occurring characters

ValueCountFrequency (%)
e 5566
16.8%
n 4651
14.0%
i 4577
13.8%
s 4484
13.5%
h 3921
11.8%
g 2195
 
6.6%
l 2025
 
6.1%
c 1650
 
5.0%
a 1246
 
3.8%
r 796
 
2.4%
Other values (14) 2003
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33114
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5566
16.8%
n 4651
14.0%
i 4577
13.8%
s 4484
13.5%
h 3921
11.8%
g 2195
 
6.6%
l 2025
 
6.1%
c 1650
 
5.0%
a 1246
 
3.8%
r 796
 
2.4%
Other values (14) 2003
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33114
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5566
16.8%
n 4651
14.0%
i 4577
13.8%
s 4484
13.5%
h 3921
11.8%
g 2195
 
6.6%
l 2025
 
6.1%
c 1650
 
5.0%
a 1246
 
3.8%
r 796
 
2.4%
Other values (14) 2003
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33114
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5566
16.8%
n 4651
14.0%
i 4577
13.8%
s 4484
13.5%
h 3921
11.8%
g 2195
 
6.6%
l 2025
 
6.1%
c 1650
 
5.0%
a 1246
 
3.8%
r 796
 
2.4%
Other values (14) 2003
 
6.0%

show_genres
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.1 KiB

show_status
Categorical

High correlation 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
running
2386 
ended
1696 
to be determined
651 

Length

Max length16
Median length7
Mean length7.5212339
Min length5

Characters and Unicode

Total characters35598
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowended
2nd rowended
3rd rowended
4th rowended
5th rowended

Common Values

ValueCountFrequency (%)
running 2386
50.4%
ended 1696
35.8%
to be determined 651
 
13.8%

Length

2024-10-31T04:37:55.216053image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-31T04:37:55.337723image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
running 2386
39.5%
ended 1696
28.1%
to 651
 
10.8%
be 651
 
10.8%
determined 651
 
10.8%

Most occurring characters

ValueCountFrequency (%)
n 9505
26.7%
e 5996
16.8%
d 4694
13.2%
r 3037
 
8.5%
i 3037
 
8.5%
u 2386
 
6.7%
g 2386
 
6.7%
t 1302
 
3.7%
1302
 
3.7%
o 651
 
1.8%
Other values (2) 1302
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 35598
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 9505
26.7%
e 5996
16.8%
d 4694
13.2%
r 3037
 
8.5%
i 3037
 
8.5%
u 2386
 
6.7%
g 2386
 
6.7%
t 1302
 
3.7%
1302
 
3.7%
o 651
 
1.8%
Other values (2) 1302
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 35598
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 9505
26.7%
e 5996
16.8%
d 4694
13.2%
r 3037
 
8.5%
i 3037
 
8.5%
u 2386
 
6.7%
g 2386
 
6.7%
t 1302
 
3.7%
1302
 
3.7%
o 651
 
1.8%
Other values (2) 1302
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 35598
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 9505
26.7%
e 5996
16.8%
d 4694
13.2%
r 3037
 
8.5%
i 3037
 
8.5%
u 2386
 
6.7%
g 2386
 
6.7%
t 1302
 
3.7%
1302
 
3.7%
o 651
 
1.8%
Other values (2) 1302
 
3.7%

show_averageRuntime
Real number (ℝ)

High correlation 

Distinct102
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.483871
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:55.479344image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q120
median43
Q350
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)30

Descriptive statistics

Standard deviation41.555692
Coefficient of variation (CV)0.93417437
Kurtosis13.212648
Mean44.483871
Median Absolute Deviation (MAD)17
Skewness3.2043791
Sum210542.16
Variance1726.8755
MonotonicityNot monotonic
2024-10-31T04:37:55.649891image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 576
 
12.2%
60 334
 
7.1%
15 312
 
6.6%
44.48387097 300
 
6.3%
30 247
 
5.2%
10 220
 
4.6%
43 140
 
3.0%
120 136
 
2.9%
3 119
 
2.5%
25 105
 
2.2%
Other values (92) 2244
47.4%
ValueCountFrequency (%)
1 6
 
0.1%
2 42
 
0.9%
3 119
2.5%
4 3
 
0.1%
5 33
 
0.7%
6 9
 
0.2%
7 52
 
1.1%
8 39
 
0.8%
9 19
 
0.4%
10 220
4.6%
ValueCountFrequency (%)
300 23
 
0.5%
242 2
 
< 0.1%
240 69
1.5%
218 1
 
< 0.1%
194 1
 
< 0.1%
184 1
 
< 0.1%
180 30
0.6%
177 4
 
0.1%
164 3
 
0.1%
163 27
 
0.6%
Distinct455
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
Minimum1944-01-20 00:00:00
Maximum2024-02-09 00:00:00
2024-10-31T04:37:55.820434image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:55.997959image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

show_ended
Date

Missing 

Distinct75
Distinct (%)4.4%
Missing3037
Missing (%)64.2%
Memory size37.1 KiB
Minimum2024-01-01 00:00:00
Maximum2024-11-09 00:00:00
2024-10-31T04:37:56.294504image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:56.487717image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct607
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:56.767672image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length250
Median length106
Mean length47.85168
Min length7

Characters and Unicode

Total characters226482
Distinct characters96
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)1.6%

Sample

1st rowhttps://www.ivi.ru/watch/nezhnost
2nd rowhttps://www.ivi.ru/watch/nezhnost
3rd rowhttps://www.ivi.ru/watch/nezhnost
4th rowhttps://www.ivi.ru/watch/nezhnost
5th rowhttps://www.ivi.ru/watch/nezhnost
ValueCountFrequency (%)
unknown 442
 
9.3%
https://flameserial.ru/season/12949 100
 
2.1%
https://abcnews.go.com/live 92
 
1.9%
https://v.qq.com/x/cover/mzc002005kvupzf.html 38
 
0.8%
https://w.mgtv.com/b/610526/20301892.html?fpa=se&lastp=so_result 36
 
0.8%
https://v.youku.com/v_nextstage/id_ebdb60223f3e44c7aadf.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle 36
 
0.8%
https://w.mgtv.com/h/600824/20020678.html 36
 
0.8%
https://www.iq.com/album/sword-and-fairy-4-2024-13ndvpx4xm1?lang=en_us 34
 
0.7%
https://v.qq.com/x/cover/mzc00200syv5tor.html 33
 
0.7%
https://www.iq.com/album/scout-hero-2023-1oipynj6bzh?lang=en_us 32
 
0.7%
Other values (597) 3854
81.4%
2024-10-31T04:37:57.203538image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 18383
 
8.1%
t 15579
 
6.9%
o 10907
 
4.8%
s 10741
 
4.7%
. 10203
 
4.5%
e 9879
 
4.4%
w 9267
 
4.1%
h 8524
 
3.8%
m 8443
 
3.7%
c 7907
 
3.5%
Other values (86) 116649
51.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 226482
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 18383
 
8.1%
t 15579
 
6.9%
o 10907
 
4.8%
s 10741
 
4.7%
. 10203
 
4.5%
e 9879
 
4.4%
w 9267
 
4.1%
h 8524
 
3.8%
m 8443
 
3.7%
c 7907
 
3.5%
Other values (86) 116649
51.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 226482
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 18383
 
8.1%
t 15579
 
6.9%
o 10907
 
4.8%
s 10741
 
4.7%
. 10203
 
4.5%
e 9879
 
4.4%
w 9267
 
4.1%
h 8524
 
3.8%
m 8443
 
3.7%
c 7907
 
3.5%
Other values (86) 116649
51.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 226482
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 18383
 
8.1%
t 15579
 
6.9%
o 10907
 
4.8%
s 10741
 
4.7%
. 10203
 
4.5%
e 9879
 
4.4%
w 9267
 
4.1%
h 8524
 
3.8%
m 8443
 
3.7%
c 7907
 
3.5%
Other values (86) 116649
51.5%

show_rating
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.1 KiB

show_weight
Real number (ℝ)

High correlation  Zeros 

Distinct98
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.205367
Minimum0
Maximum100
Zeros138
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:57.378301image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median22
Q348
95-th percentile94
Maximum100
Range100
Interquartile range (IQR)42

Descriptive statistics

Standard deviation30.094471
Coefficient of variation (CV)0.96440049
Kurtosis-0.51337109
Mean31.205367
Median Absolute Deviation (MAD)16
Skewness0.89729465
Sum147695
Variance905.67717
MonotonicityNot monotonic
2024-10-31T04:37:57.549841image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 722
 
15.3%
8 258
 
5.5%
3 198
 
4.2%
12 181
 
3.8%
4 166
 
3.5%
23 148
 
3.1%
0 138
 
2.9%
18 121
 
2.6%
10 104
 
2.2%
1 103
 
2.2%
Other values (88) 2594
54.8%
ValueCountFrequency (%)
0 138
 
2.9%
1 103
 
2.2%
2 52
 
1.1%
3 198
 
4.2%
4 166
 
3.5%
5 50
 
1.1%
6 722
15.3%
7 69
 
1.5%
8 258
 
5.5%
9 79
 
1.7%
ValueCountFrequency (%)
100 3
 
0.1%
99 14
 
0.3%
98 35
0.7%
97 38
0.8%
96 19
 
0.4%
95 79
1.7%
94 78
1.6%
93 29
 
0.6%
92 15
 
0.3%
91 8
 
0.2%

show_network
Unsupported

Missing  Rejected  Unsupported 

Missing4217
Missing (%)89.1%
Memory size37.1 KiB

show_summary
Text

Missing 

Distinct591
Distinct (%)14.9%
Missing771
Missing (%)16.3%
Memory size37.1 KiB
2024-10-31T04:37:57.962519image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1931
Median length631
Mean length382.40106
Min length50

Characters and Unicode

Total characters1515073
Distinct characters333
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)1.8%

Sample

1st row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
2nd row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
3rd row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
4th row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
5th row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
ValueCountFrequency (%)
the 15036
 
6.0%
and 9009
 
3.6%
to 7101
 
2.8%
of 7044
 
2.8%
a 6969
 
2.8%
in 4508
 
1.8%
is 2721
 
1.1%
with 2625
 
1.1%
her 2565
 
1.0%
his 2301
 
0.9%
Other values (8256) 189929
76.0%
2024-10-31T04:37:58.612780image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245491
16.2%
e 144650
 
9.5%
a 95420
 
6.3%
t 95390
 
6.3%
n 88736
 
5.9%
i 87743
 
5.8%
o 83919
 
5.5%
s 76275
 
5.0%
r 71755
 
4.7%
h 64182
 
4.2%
Other values (323) 461512
30.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1515073
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
245491
16.2%
e 144650
 
9.5%
a 95420
 
6.3%
t 95390
 
6.3%
n 88736
 
5.9%
i 87743
 
5.8%
o 83919
 
5.5%
s 76275
 
5.0%
r 71755
 
4.7%
h 64182
 
4.2%
Other values (323) 461512
30.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1515073
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
245491
16.2%
e 144650
 
9.5%
a 95420
 
6.3%
t 95390
 
6.3%
n 88736
 
5.9%
i 87743
 
5.8%
o 83919
 
5.5%
s 76275
 
5.0%
r 71755
 
4.7%
h 64182
 
4.2%
Other values (323) 461512
30.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1515073
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
245491
16.2%
e 144650
 
9.5%
a 95420
 
6.3%
t 95390
 
6.3%
n 88736
 
5.9%
i 87743
 
5.8%
o 83919
 
5.5%
s 76275
 
5.0%
r 71755
 
4.7%
h 64182
 
4.2%
Other values (323) 461512
30.5%

show_updated
Real number (ℝ)

Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7157408 × 109
Minimum1.6983432 × 109
Maximum1.7303334 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-31T04:37:58.781572image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.6983432 × 109
5-th percentile1.7048193 × 109
Q11.7066994 × 109
median1.7138339 × 109
Q31.7253571 × 109
95-th percentile1.7302199 × 109
Maximum1.7303334 × 109
Range31990198
Interquartile range (IQR)18657711

Descriptive statistics

Standard deviation9287441.5
Coefficient of variation (CV)0.0054130795
Kurtosis-1.4310003
Mean1.7157408 × 109
Median Absolute Deviation (MAD)7747315
Skewness0.30513815
Sum8.1206013 × 1012
Variance8.625657 × 1013
MonotonicityNot monotonic
2024-10-31T04:37:58.957105image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1723133542 100
 
2.1%
1707133992 38
 
0.8%
1706192291 36
 
0.8%
1706282249 36
 
0.8%
1705897985 36
 
0.8%
1706797142 34
 
0.7%
1711774278 33
 
0.7%
1706339205 32
 
0.7%
1706957455 30
 
0.6%
1706023757 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
1698343176 4
0.1%
1699173762 4
0.1%
1699196321 3
0.1%
1700067953 1
 
< 0.1%
1701776723 7
0.1%
1703096478 4
0.1%
1703320852 7
0.1%
1703404987 3
0.1%
1703852377 4
0.1%
1703934794 4
0.1%
ValueCountFrequency (%)
1730333374 12
0.3%
1730330131 3
 
0.1%
1730329160 6
 
0.1%
1730328212 4
 
0.1%
1730324012 8
 
0.2%
1730319309 3
 
0.1%
1730308891 22
0.5%
1730308696 23
0.5%
1730306723 12
0.3%
1730304073 1
 
< 0.1%

show_links
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size37.1 KiB

extraction_date
Categorical

High correlation 

Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
2024-01-26
 
301
2024-01-19
 
265
2024-01-11
 
230
2024-01-18
 
217
2024-01-25
 
214
Other values (26)
3506 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters47330
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-01
2nd row2024-01-01
3rd row2024-01-01
4th row2024-01-01
5th row2024-01-01

Common Values

ValueCountFrequency (%)
2024-01-26 301
 
6.4%
2024-01-19 265
 
5.6%
2024-01-11 230
 
4.9%
2024-01-18 217
 
4.6%
2024-01-25 214
 
4.5%
2024-01-08 210
 
4.4%
2024-01-22 190
 
4.0%
2024-01-01 188
 
4.0%
2024-01-24 179
 
3.8%
2024-01-04 173
 
3.7%
Other values (21) 2566
54.2%

Length

2024-10-31T04:37:59.112969image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-01-26 301
 
6.4%
2024-01-19 265
 
5.6%
2024-01-11 230
 
4.9%
2024-01-18 217
 
4.6%
2024-01-25 214
 
4.5%
2024-01-08 210
 
4.4%
2024-01-22 190
 
4.0%
2024-01-01 188
 
4.0%
2024-01-24 179
 
3.8%
2024-01-04 173
 
3.7%
Other values (21) 2566
54.2%

Most occurring characters

ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 47330
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 47330
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 47330
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Interactions

2024-10-31T04:37:41.681053image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:32.807856image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:33.976711image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:35.355388image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:36.457653image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:37.609751image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:38.958344image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:40.388022image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:41.882023image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:32.992292image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:34.100994image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:35.483724image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:36.603110image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:37.756520image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:39.097490image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:40.591514image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:42.037764image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:33.129920image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:34.294774image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:35.619713image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:36.748045image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:37.905440image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:39.272056image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:40.777021image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:42.203336image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:33.253719image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:34.486228image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:35.747020image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:36.906633image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:38.100601image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:39.469721image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:40.910627image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:42.339463image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:33.385511image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:34.617877image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:35.936826image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:37.068201image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:38.241190image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:39.601175image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:41.100795image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:42.537636image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:33.523787image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:34.932069image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:36.081126image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:37.214098image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:38.444680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:39.793915image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:41.239422image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:42.672565image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:33.654510image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:35.067705image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:36.208115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:37.348451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:38.619214image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:39.996137image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:41.366084image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:42.839155image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:33.795873image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:35.201479image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:36.336770image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:37.474114image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:38.815714image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:40.233582image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-31T04:37:41.542964image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-10-31T04:37:59.217686image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
airdateextraction_dateidnumberruntimeseasonshow_averageRuntimeshow_idshow_languageshow_statusshow_typeshow_updatedshow_weighttype
airdate1.0001.0000.1800.0000.0550.0900.0700.0910.1090.1620.1100.1790.1020.062
extraction_date1.0001.0000.1800.0000.0550.0900.0700.0910.1090.1620.1100.1790.1020.062
id0.1800.1801.0000.0630.0170.2270.0190.4500.2240.2080.4010.290-0.3870.216
number0.0000.0000.0631.000-0.149-0.095-0.1700.0670.1090.0920.1010.019-0.1171.000
runtime0.0550.0550.017-0.1491.0000.3170.9410.0070.2340.1980.2770.0760.0770.078
season0.0900.0900.227-0.0950.3171.0000.361-0.3500.4360.4110.8300.4920.2080.000
show_averageRuntime0.0700.0700.019-0.1700.9410.3611.000-0.0200.2230.2010.2710.1150.0930.000
show_id0.0910.0910.4500.0670.007-0.350-0.0201.0000.2670.2880.228-0.156-0.7070.056
show_language0.1090.1090.2240.1090.2340.4360.2230.2671.0000.5540.3030.3010.2580.160
show_status0.1620.1620.2080.0920.1980.4110.2010.2880.5541.0000.5320.4020.2780.027
show_type0.1100.1100.4010.1010.2770.8300.2710.2280.3030.5321.0000.2170.1900.083
show_updated0.1790.1790.2900.0190.0760.4920.115-0.1560.3010.4020.2171.0000.2800.000
show_weight0.1020.102-0.387-0.1170.0770.2080.093-0.7070.2580.2780.1900.2801.0000.063
type0.0620.0620.2161.0000.0780.0000.0000.0560.1600.0270.0830.0000.0631.000

Missing values

2024-10-31T04:37:43.100076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-31T04:37:43.683460image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-10-31T04:37:44.030805image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idurlnameseasonnumbertypeairdateairtimeairstampruntimeratingsummarylinks_selflinks_show_hreflinks_show_nameshow_idshow_urlshow_nameshow_typeshow_languageshow_genresshow_statusshow_averageRuntimeshow_premieredshow_endedshow_officialSiteshow_ratingshow_weightshow_networkshow_summaryshow_updatedshow_linksextraction_date
02730586https://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1Серия 121.0regular2024-01-012024-01-01T00:00:00+00:0023.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730586https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
12730587https://www.tvmaze.com/episodes/2730587/neznost-2x02-seria-2Серия 222.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730587https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
22730588https://www.tvmaze.com/episodes/2730588/neznost-2x03-seria-3Серия 323.0regular2024-01-012024-01-01T00:00:00+00:0019.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730588https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
32730589https://www.tvmaze.com/episodes/2730589/neznost-2x04-seria-4Серия 424.0regular2024-01-012024-01-01T00:00:00+00:0021.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730589https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
42730590https://www.tvmaze.com/episodes/2730590/neznost-2x05-seria-5Серия 525.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730590https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
52730591https://www.tvmaze.com/episodes/2730591/neznost-2x06-seria-6Серия 626.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730591https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
62730592https://www.tvmaze.com/episodes/2730592/neznost-2x07-seria-7Серия 727.0regular2024-01-012024-01-01T00:00:00+00:0020.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730592https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
72730593https://www.tvmaze.com/episodes/2730593/neznost-2x08-seria-8Серия 828.0regular2024-01-012024-01-01T00:00:00+00:0019.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730593https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
82730594https://www.tvmaze.com/episodes/2730594/neznost-2x09-seria-9Серия 929.0regular2024-01-012024-01-01T00:00:00+00:0018.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730594https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
92730595https://www.tvmaze.com/episodes/2730595/neznost-2x10-seria-10Серия 10210.0regular2024-01-012024-01-01T00:00:00+00:0019.0{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2730595https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedrussian[Drama, Comedy, Romance]ended19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost{'average': None}10NoneNone1704215354{'self': {'href': 'https://api.tvmaze.com/shows/51908'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2730595', 'name': 'Серия 10'}}2024-01-01
idurlnameseasonnumbertypeairdateairtimeairstampruntimeratingsummarylinks_selflinks_show_hreflinks_show_nameshow_idshow_urlshow_nameshow_typeshow_languageshow_genresshow_statusshow_averageRuntimeshow_premieredshow_endedshow_officialSiteshow_ratingshow_weightshow_networkshow_summaryshow_updatedshow_linksextraction_date
47232920526https://www.tvmaze.com/episodes/2920526/dromkakar-utomlands-1x04-avsnitt-4Avsnitt 414.0regular2024-01-3100:002024-01-31T23:00:00+00:0045.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2920526https://api.tvmaze.com/shows/73778Drömkåkar utomlands73778https://www.tvmaze.com/shows/73778/dromkakar-utomlandsDrömkåkar utomlandsRealityswedish[]to be determined45.0000002024-01-10Nonehttps://www.tv4play.se/program/9e5573b08abbda332d28/dromkakar-utomlands{'average': None}3None<p>For two years, we get to follow Swedes who build and renovate the houses they dreamed of, abroad. But the journey to the dream home is not always straight.</p>1718874160{'self': {'href': 'https://api.tvmaze.com/shows/73778'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2920530', 'name': 'Avsnitt 8'}}2024-01-31
47242761042https://www.tvmaze.com/episodes/2761042/dimension-20-21x04-under-pressureUnder Pressure214.0regular2024-01-3119:002024-02-01T00:00:00+00:0044.401026{'average': None}<p>The Bad Kids realize how much work they'll be balancing this year. Adaine gets a job.</p>https://api.tvmaze.com/episodes/2761042https://api.tvmaze.com/shows/56531Dimension 2056531https://www.tvmaze.com/shows/56531/dimension-20Dimension 20Game Showenglish[Comedy, Adventure, Fantasy]running107.0000002018-09-12Nonehttps://www.dropout.tv/dimension-20{'average': None}82None<p>Heed the call of adventure and enter <b>Dimension 20</b> where Game Master Brennan Lee Mulligan, joined by comedians and pro gamers, blends comedy with tabletop RPGs.</p>1729775734{'self': {'href': 'https://api.tvmaze.com/shows/56531'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3034896', 'name': 'K's Anatomy'}}2024-01-31
47252794533https://www.tvmaze.com/episodes/2794533/the-daily-report-with-john-dickerson-2024-01-31-episode-18Episode 18202418.0regular2024-01-3119:002024-02-01T00:00:00+00:0060.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2794533https://api.tvmaze.com/shows/75261The Daily Report with John Dickerson75261https://www.tvmaze.com/shows/75261/the-daily-report-with-john-dickersonThe Daily Report with John DickersonNewsenglish[]running60.0000002022-09-06Nonehttps://www.cbsnews.com/prime-time-with-john-dickerson/{'average': None}8None<p>John Dickerson provides in-depth reporting on news stories and interviews newsmakers.</p>1722688947{'self': {'href': 'https://api.tvmaze.com/shows/75261'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2966145', 'name': 'Episode 140'}}2024-01-31
47262833048https://www.tvmaze.com/episodes/2833048/abc-prime-with-linsey-davis-2024-01-31-episode-23Episode 23202423.0regular2024-01-3119:002024-02-01T00:00:00+00:0090.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2833048https://api.tvmaze.com/shows/76215ABC Prime with Linsey Davis76215https://www.tvmaze.com/shows/76215/abc-prime-with-linsey-davisABC Prime with Linsey DavisNewsenglish[]running90.0000002020-02-17Nonehttps://abcnews.go.com/Live{'average': None}6None<p>Providing prime-time context and analysis of the day's top stories, as well as in-depth reporting and storytelling from around the country and the globe.</p>1728235929{'self': {'href': 'https://api.tvmaze.com/shows/76215'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3013782', 'name': 'Episode 195'}}2024-01-31
47272750457https://www.tvmaze.com/episodes/2750457/camilla-hamids-bakresa-marocko-1x02-avsnitt-2Avsnitt 212.0regular2024-01-3102:002024-02-01T01:00:00+00:0044.401026{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2750457https://api.tvmaze.com/shows/73963Camilla Hamids bakresa: Marocko73963https://www.tvmaze.com/shows/73963/camilla-hamids-bakresa-marockoCamilla Hamids bakresa: MarockoRealityswedish[]running44.4838712024-01-24Nonehttps://www.svtplay.se/camilla-hamids-bakresa-marocko{'average': None}6None<p>Come along to Camilla's Moroccan family where she gets to learn about the Moroccan baking culture together to understand more about where she belongs. Camilla has always felt too Swedish in Morocco and too Moroccan in Sweden and never really felt 100% at home anywhere. With this program, she hopes not only to offer new exciting baking pleasure, but also understanding and recognition.</p>1706117901{'self': {'href': 'https://api.tvmaze.com/shows/73963'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2750460', 'name': 'Avsnitt 5'}}2024-01-31
47282941639https://www.tvmaze.com/episodes/2941639/trafficked-with-mariana-van-zeller-4x03-body-partsBody Parts43.0regular2024-01-3121:002024-02-01T02:00:00+00:0060.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2941639https://api.tvmaze.com/shows/49496Trafficked with Mariana van Zeller49496https://www.tvmaze.com/shows/49496/trafficked-with-mariana-van-zellerTrafficked with Mariana van ZellerDocumentaryenglish[Crime]to be determined62.0000002020-12-02Nonehttps://www.nationalgeographic.com/tv/shows/trafficked-with-mariana-van-zeller{'average': 7.8}86{'id': 42, 'name': 'National Geographic', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': 'https://www.nationalgeographic.com/tv/'}<p>Armed with National Geographic's trademark inside access, <b>Trafficked with Mariana van Zeller</b> takes viewers on a journey inside the most dangerous black markets on the planet. Each investigation in the eight-part series embeds with Peabody and duPont Award-winning journalist Mariana van Zeller as she explores the complex and often violent inner workings of a smuggling network. While she dives deeper and deeper into these underworlds, Mariana reveals - with characteristic boldness and empathy - that the people operating these trafficking rings are often a lot more like us than we realize.</p>1720942651{'self': {'href': 'https://api.tvmaze.com/shows/49496'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2941650', 'name': 'Caught in an African Coup'}}2024-01-31
47292732350https://www.tvmaze.com/episodes/2732350/alle-elsker-david-5x15-viva-barcelona¡Viva Barcelona!515.0regular2024-01-3103:002024-02-01T02:00:00+00:0021.000000{'average': None}<p>The gang is in Barcelona and going to see Ingrid play a match. Andrea confronts her father about his future plans with Louise.</p>https://api.tvmaze.com/episodes/2732350https://api.tvmaze.com/shows/54476Alle Elsker David54476https://www.tvmaze.com/shows/54476/alle-elsker-davidAlle Elsker DavidRealitynorwegian[]to be determined22.0000002021-03-08Nonehttps://play.tv2.no/programmer/underholdning/alle-elsker-david{'average': None}11None<p>We follow manager David Eriksen and his charming but untraditional family. In David's new company, the pace is high and the drop is great.</p>1714772507{'self': {'href': 'https://api.tvmaze.com/shows/54476'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2732353', 'name': 'Sykemelding og flyttemelding'}}2024-01-31
47302765084https://www.tvmaze.com/episodes/2765084/disasterinas-my-drag-is-valid-1x15-luka-ghostLuka Ghost115.0regular2024-01-3100:002024-02-01T04:00:00+00:0044.401026{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2765084https://api.tvmaze.com/shows/73167Disasterina's My Drag Is Valid73167https://www.tvmaze.com/shows/73167/disasterinas-my-drag-is-validDisasterina's My Drag Is ValidTalk Showenglish[]running24.0000002023-10-25Nonehttps://www.outtvgo.com/details/TV_SHOW/collection/6339796989112/disasterinas-my-drag-is-valid{'average': None}6None<p>Disasterina, star of Sado Psychiatrist and The Boulet Brothers' Dragula, interviews a variety of drag artists to showcase the different styles of drag in performance, looks, and personalities. From seasoned underground fan favorites to the lesser known newbies, Disasterina and her talented guests prove that ALL drag is valid.</p>1728971819{'self': {'href': 'https://api.tvmaze.com/shows/73167'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3029154', 'name': 'Gothess Jasmin'}}2024-01-31
47312848032https://www.tvmaze.com/episodes/2848032/fox-news-night-2024-01-31-episode-22Episode 22202422.0regular2024-01-3123:002024-02-01T04:00:00+00:0060.000000{'average': None}No summary availablehttps://api.tvmaze.com/episodes/2848032https://api.tvmaze.com/shows/76581Fox News @ Night76581https://www.tvmaze.com/shows/76581/fox-news-nightFox News @ NightNewsenglish[]running60.0000002017-10-30Nonehttps://www.foxnews.com/shows/fox-news-night{'average': None}8{'id': 185, 'name': 'Fox News Channel', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': 'https://www.foxnews.com/'}<p><b>Fox News @ Night</b> is a live hour of hard news and analysis of the most compelling stories from Washington and across the country.</p>1716912888{'self': {'href': 'https://api.tvmaze.com/shows/76581'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/2889864', 'name': 'Episode 132'}}2024-01-31
47322751926https://www.tvmaze.com/episodes/2751926/the-tonight-show-starring-jimmy-fallon-2024-01-31-arnold-schwarzenegger-kathryn-newton-the-lemon-twigsArnold Schwarzenegger, Kathryn Newton, The Lemon Twigs202417.0regular2024-01-3123:352024-02-01T04:35:00+00:0060.000000{'average': None}<p>Actor Arnold Schwarzenegger; actress Kathryn Newton; The Lemon Twigs perform.</p>https://api.tvmaze.com/episodes/2751926https://api.tvmaze.com/shows/718The Tonight Show Starring Jimmy Fallon718https://www.tvmaze.com/shows/718/the-tonight-show-starring-jimmy-fallonThe Tonight Show Starring Jimmy FallonTalk Showenglish[Comedy]running60.0000002014-02-17Nonehttp://www.nbc.com/the-tonight-show{'average': 4.4}98{'id': 1, 'name': 'NBC', 'country': {'name': 'United States', 'code': 'US', 'timezone': 'America/New_York'}, 'officialSite': 'https://www.nbc.com/'}<p>Emmy Award and Grammy Award winner Jimmy Fallon brought NBC's "The Tonight Show" back to its New York origins when he launched <b>The Tonight Show Starring Jimmy Fallon </b>from Rockefeller Center. Fallon puts his own stamp on the storied NBC late-night franchise with his unique comedic wit, on-point pop culture awareness, welcoming style and impeccable taste in music with the award-winning house band, The Roots.</p>1730212150{'self': {'href': 'https://api.tvmaze.com/shows/718'}, 'previousepisode': {'href': 'https://api.tvmaze.com/episodes/3034921', 'name': 'Olivia Rodrigo, Keri Russell, Andrea Bocelli, Lauren Daigle'}, 'nextepisode': {'href': 'https://api.tvmaze.com/episodes/3038485', 'name': 'Salma Hayek Pinault, David Chang, Kelsea Ballerini'}}2024-01-31